Patent
Hidden Markov Model Based Handwriting/Calligraphy Generation
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TLDR
In this paper, a method for handwritten character generation using Hidden Markov Models (HMM) is described. But the HMM can be adapted using a technique such as a maximum a posterior technique, a maximum likelihood linear regression technique or an Eigen-space technique.Citations
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References
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Patent
Handwriting recognition system and method
TL;DR: The authors proposed a system for recognizing handwritten characters, including preprocessing apparatus for generating a set of features for each handwritten character, a neural network disposed for operating on sparse data structures of those features, and post-processing for adjusting those confidence values and for selecting a character symbol consistent with external knowledge about handwritten characters and the language they are written in.
Patent
Methods and apparatuses for handwriting recognition
TL;DR: In this article, a handwriting recognition system for ideographic characters and other characters based on subcharacter hidden Markov models is presented, where the characters are modeled using a sequence of subcharacter models and by using two-dimensional geometric layout models of the subcharacters.
Patent
Trie structure based method and apparatus for indexing and searching handwritten databases with dynamic search sequencing
Walid G. Aref,Daniel Barbará +1 more
TL;DR: In this paper, a method of searching for one of a plurality of objects that match an input sequence of handwritten objects is provided, where the objects are modeled by concatenating members of a set of component objects.
Patent
Continuous parameter hidden Markov model approach to automatic handwriting recognition
TL;DR: A computer-based system and method for handwriting recognition using hidden Markov models was proposed in this article.The present system includes a preprocessor, a front end, and a modeling component.
Patent
A system and method for automatic handwriting recognition with a writer-independent chirographic label alphabet
TL;DR: In this article, an automatic handwriting recognition system where each written (chirographic) manifestation of each character is represented by a statistical model (called a hidden Markov model) is described.